Discovery of action patterns in task-oriented learning processes

Xiaokang Zhou, Jian Chen, Qun Jin

    Research output: Contribution to journalArticle

    4 Citations (Scopus)

    Abstract

    In this study, in order to support and facilitate the web-based learning, we concentrate on user learning behavior pattern discovery in a task-oriented learning process. Based on a hierarchical graph model which can describe relations among learning actions, learning activities, learning sub-tasks and learning tasks, we introduce the formal definitions for Learning Action Pattern and Goal-driven Learning Group to discover and represent users' learning behavior patterns within a learning task process. Two integrated algorithms are developed to calculate and generate the Learning Action Patterns for an individual user and the Goal-driven Learning Groups for a number of users, which can benefit sharing of learning activities and improve learning efficiency in e-learning environments. Finally, the design of a prototype system with experiment results is discussed.

    Original languageEnglish
    Pages (from-to)121-130
    Number of pages10
    JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume8167 LNCS
    DOIs
    Publication statusPublished - 2013

    Fingerprint

    Learning Process
    Experiments
    Learning
    Web-based Learning
    Pattern Discovery
    Learning Environment
    Graph Model
    Electronic Learning
    Hierarchical Model
    Sharing
    Prototype

    Keywords

    • Learning Activity
    • Learning Pattern
    • Learning Task
    • User Behavior Modeling

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

    Cite this

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